1. Field of the Invention
The present invention relates to detection of abnormal operation of manufacturing apparatuses used in manufacturing processes of semiconductor integrated circuits. In particular, the invention relates to a control system for a group of manufacturing apparatuses and a method for controlling the manufacturing apparatuses. The control system identifies a reason for a failure and achieves an optimal operation of the manufacturing apparatus.
2. Description of the Related Art
One of the most important problems in the production of a semiconductor device such as a large-scale integrated circuit (LSI) is to improve the yield rate. Improving the yield rate increases productivity. In order to improve the yield rate, it is important to analyze a yield loss and thus, analyze a manufacturing process, a manufacturing apparatus or a design condition so as to determine the cause of the yield loss. Then, remedial measures can be taken to avoid or prevent yield loss. However, the LSI is produced, for example, by a sequence of several hundred processes and manufacturing apparatuses. Accordingly, once a failure occurs in the LSI, it is generally very difficult to detect a reason for the failure.
Test results of electrical characteristics of a wafer, conducted after completion of a wafer process in the LSI production, sometimes give an important clue for identifying the reason for the failure. This is because the wafer tests are performed on a wafer after completion of the production process. The results of the wafer test are mapped and displayed with respect to positions on a wafer surface, and failure positions on the wafer surface are detected. A representative example of such a map is a fail bit map (FSM) acquired in a memory product. In a logic product, a merged memory logic product and the like, a pass/fail map is acquired by the test where a nondefective chip (pass) or a defective chip (fail) are mapped and displayed.
A failure distribution on the wafer surface may be classified into two types in broad terms, i.e., a random failure in which failures are evenly distributed regardless of positions on the wafer surface; and a clustering failure in which the failures disproportionately occur in a portion of the wafer surface. In many cases, the clustering failure is caused by a systematic factor attributable to the manufacturing process, the manufacturing apparatus and the like. The clustering failure is a major reason for a decrease in the yield rate. The failure attributable to the manufacturing process, manufacturing apparatus and the like generates a failure pattern on the wafer surface inherent in the manufacturing process and the manufacturing apparatus. Hence, a pattern analysis of the clustering failure is a clue for identifying the reason for the occurrence of the failure.
Detection of the reason for a failure in the production of an electronic device such as the LSI is implemented by tracing back into the manufacturing record of the LSI for wafers or manufacturing lots in which the same clustering failure has occurred. For example, a search is made as to whether or not there is a commonly used manufacturing apparatus for processed wafers on which the same clustering failures have occurred in the same manufacturing process. For detecting the reason for a failure, there has been proposed a method of implementing a significance test for the manufacturing apparatuses regarding characteristic quantities obtained by quantifying the clustering failures (refer to Japanese Patent Laid-Open No. 2002-359266).
A manufacturing apparatus includes a unit which collects and records operation requirement information such as conditions and set values of the manufacturing apparatus during processing of wafers. The operation requirement information of the manufacturing apparatus is referred to as an apparatus parameter. Detail analysis of apparatus parameters enables identification of a name of a manufacturing apparatus in which a failure occurs, as well as an abnormal operation portion of the manufacturing apparatus. Therefore, measures to prevent the occurrence of the failure may be provided at an early stage. Even statistical tests, by use of apparatus parameters themselves, however, sometimes have a problem that does not lead to the identification of a cause of the abnormality. Also, beginning a search for a cause of a failure, after detecting the failure from wafer test results, creates a problem in some cases in that the feed back to the manufacturing process is too late. In addition, extraction and the maintenance of operation requirements of a manufacturing apparatus for manufacturing products at a high yield are extremely difficult because the number of apparatus parameters is huge and the apparatus parameters are correlated with each other.